ANTICANCER RESEARCH 35: 3253-3266 (2015)

Differential Regulation in Fibroblasts in Co-culture with Keratinocytes and Head and Neck SCC Cells

MALIN HAKELIUS1, DANIEL SAIEPOUR1, HANNA GÖRANSSON2, KRISTOFER RUBIN3, BENGT GERDIN1 and DANIEL NOWINSKI1

Departments of 1Surgical Sciences, Plastic Surgery and 3Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden; 2Array Facility, Department of Medical Sciences, Uppsala University, Uppsala, Sweden

Abstract. Background: While carcinoma-associated growth. In , this microenvironment, or tumor stroma, fibroblasts (CAFs) support tumorigenesis, normal constitutes the backbone of the tumor and is essential for the fibroblasts suppress tumor progression. Mechanisms behind cohesiveness of the tumor tissue the tumor’s ability to thrive conversion of fibroblasts into a CAF are largely (1). This stroma has considerable similarities with that of unrevealed. Materials and Methods: Transwell co-cultures non-malignant repair processes that are characterized by with fibroblasts in collagen gels and squamous- activation of fibroblasts and neoformation of stromal tissue, carcinoma (SCC) cells or normal oral keratinocytes (NOKs) which has led to the concept of a tumor as a "wound that in inserts. Differences in fibroblast global never heals" (2). were analyzed using Affymetrix arrays and subsequent A fibroblast phenotype characterized by expression of functional annotation and cluster analysis, as well as gene alpha-smooth muscle actin (SMA), platelet-derived growth set enrichment analysis were performed. Results: There were factor receptor-beta (PDGFR-β) and the pericyte marker 52 up-regulated and 30 down-regulated transcript IDs neuron glial antigen 2 (NG2) is regarded as a key cell in the (>2-fold, p<0.05) in fibroblasts co-cultured with SCC tumor stroma (3). Accordingly, this phenotype has been compared to NOKs. Functional analysis demonstrated an denoted “-associated fibroblast”, CAF. It has been enrichment of collagen-related . There were similarities proposed that the CAF phenotype is the result of a reciprocal with gene sets reflecting a non-specific, innate–type response signaling between tumor cells and stromal fibroblasts (3). with activation of both pathways and connective However, the nature of such signaling is only partially tissue turnover. Conclusion: There were distinct differences studied as there exist differences in signaling between benign in fibroblast gene expression between the co-culture types. proliferating keratinocytes and stromal cells in a healing Many were in genes related to an innate-type of response wound and the corresponding process in malignant tissue. and to connective tissue turnover. Two phenomena are worth mentioning. First, keratinocytes from the wound edge transiently exhibit many similarities to Tumors arise as consequences of genetic alterations in their transformed counterparts in squamous-cell carcinomas normal cells, which -in turn- result in a loss of cellular (SCCs) (4). Second, the stroma of a healing wound also growth control. In addition, tumor progression requires an contains cells with characteristics similar to those of the aberrant microenvironment that supports further tumor CAFs. Thus, similarities, as well as differences, in the interaction between the malignant keratinocyte phenotype and stromal cells, compared to the interaction between Abbreviations: CAF: Carcinoma associated fibroblasts; NOKs: benign keratinocytes and stromal cells, may be expected. normal oral keratinocytes; SCC: squamous cell carcinoma. The origin of the CAFs has not been established with certainty. Current information suggests that CAFs may be Correspondence to: Daniel Nowinski, MD, Ph.D., Department of derived from a variety of sources. Three main hypotheses Plastic and Maxillofacial Surgery, Uppsala University Hospital, 751 have been proposed. First, it has been suggested that CAFs 85 Uppsala, Sweden. Tel: +46 738664625, e-mail: daniel. [email protected] are recruited locally from resident cells in the vicinity of a growing and spreading tumor, including normal tissue Key Words: Head and neck cancer, keratinocytes, differential gene fibroblasts and tissue mesenchymal stem cells (MSCs). regulation, array. Second, bone marrow-derived cells with an ability to

0250-7005/2015 $2.00+.40 3253 ANTICANCER RESEARCH 35: 3253-3266 (2015) differentiate into fibroblast have been shown to Co-culture. Fibroblasts were cultured in collagen gels. Briefly, a migrate to areas of proliferating tumor cells. Finally, other cold solution of 1.6 ml collagen type I (Vitrogen, Cohesion, Palo cell types, e.g. pericytes, myoepithelial cells and endothelial Alto, CA, USA), 0.15 ml (10×) Hank’s balanced salt solution (10xHBSS) and 0.15 ml fetal bovine serum (FBS) with or without cells, are thought to transdifferentiate towards a tumor fibroblasts (2×105/well) was pH-adjusted to pH 7.4 with 5 M NaOH fibroblast-like population (3). and added to 6-well plates. After polymerization at 37˚C, 2 ml Using co-culture systems we have previously shown that DMEM with 10% bovine calf serum (HyClone) was added to each normal keratinocytes from both skin and the oral cavity well. Normal oral keratinocytes or malignant keratinocytes (UT- decrease profibrotic characteristics of fibroblasts through SCC-87), in passage 16 or 17, were seeded in Falcon polyurethane humoral mechanisms, which -at least in part- involve release cell culture inserts (4.0 μm pore diameter). The inserts were pre- of interleukin-1α (IL-1α) from the epithelial cells (5-7). incubated with a mixture of 10 μg/ml bovine plasma (Gibco BRL/Life Technology, Paisley, UK), 30 μg/ml bovine Furthermore, this down-regulation was more pronounced in collagen (Vitrogen) and 10 μg/ml bovine serum albumin (Sigma) co-cultures with normal oral keratinocytes (NOKs) than with for 2 h at 37˚C. NOKs and malignant oral keratinocytes were seeded oral SSC cells (5). This observation forms the basis for the in inserts, both in DMEM: HAM’s F12 (4:1) supplemented with present study, which investigates the differential effect of 5 μg/ml Zn-free (Sigma Chemical Co.), 2 nM 3,3’,5-triido- NOKs and SCC on overall fibroblast gene expression D-thyronine (Sigma), 0.4 μg/ml hydrocortisone (Sigma), 0.1 nM through humoral communication, utilizing a conventional cholera toxin (Sigma), 10 ng/ml EGF (Austral Biologicals, San array approach. The aim of the study was to reveal to what Ramon, CA, USA), 24 μg/ml adenine, 10% fetal bovine serum (HyClone) and 50 μg/ml gentamicin. After 24 h, the medium was extent there exist differences in overall gene expression at a changed in wells and in inserts to 2 ml DMEM/Ham’s F12 (4:1) cluster level that reflects qualitative differences in fibroblast supplemented with 0.5% FCS in each. Inserts and wells with cell response after a humoral interaction with benign versus collagen gels were combined and propagated as co-cultures for an malignant epithelial cells. An additional aim is to determine additional 48 h. As controls, 0.15×106 fibroblasts were seeded in whether such differences exhibit similarities with publicly inserts instead of keratinocytes. Experiments were performed with presented gene expression profiles or molecular signatures. different seeding concentrations of NOKs and malignant keratinocytes and the number of cells was assessed with a cell- Materials and Methods counter (Z2 Cell and Particle Counter; Beckman Coulter AB, City, CA, USA) after 48 h. The reason for the different seeding-numbers for normal and malignant cells was to compensate for an observed Cells. A head and neck SCC (UT-SCC-87) cell line established at higher proliferation of malignant cells. After titration with different the University of Turku, Finland, was used in this study. The cell seeding densities, concentrations of 0.30×106 for NOKs and line was established from a previously untreated primary tumor of 0.16×106 for malignant cells were chosen for the experiments. In the mobile tongue in a 29-year-old female patient presenting with a this way, the average cell number at the termination of the co- T3N1M0 grade 1 SCC. The methods used in establishing and cultures was 0.45×106 for NOKs and 0.43×106 for malignant cells, characterizing the cell line have been described previously (8, 9). and a cell-density of about 80% was reached in all samples at the NOKs were obtained from the gingiva of a 28-year-old, previously end of the co-culture experiments. healthy, non-smoking male. Human primary dermal fibroblasts were obtained from patients undergoing reconstructive breast surgery at RNA extraction. Collagen gels were dissolved and RNA was the Department of Plastic Surgery, Uppsala University Hospital. extracted using a modification of the one-step-phenol-chloroform Fibroblasts from one healthy female were used for the experiments. method (11). Gels were dissolved in TRIzol reagent (Life Approval from the local ethics committee (Uppsala University) was Technology) under extensive vortex mixing. The amount and the obtained (Dnr 2005:332). This approval entails written informed quality of RNA were determined using the Agilent Bioanalyzer consent and written patient information. 2100 (Agilent Technology, Kista, Sweden).

Cellular isolation and culture. Mucosal samples were treated with Microarray expression analysis. Three different experiments with dispase and the epithelium was mechanically separated from the duplicates were done with fibroblasts, NOKs or SCC cells in the underlying lamina propria. NOKs were isolated as previously described inserts, i.e. 18 different experiments. Collagen gels from these (10). Following mechanical fragmentation, the epithelial layer was duplicates were pooled before extraction of RNA, leaving nine treated with trypsin and keratinocytes were propagated on irradiated samples from three different groups. RNA concentration was 3T3 feeder cells in DMEM: HAMs F12 (4:1) supplemented with measured with the ND-1000 spectrophotometer (NanoDrop 5 μg/ml Zn-free insulin (Sigma Chemical Co., St. Louis, MO, USA), Technologies, Wilmington, DE, USA) and RNA quality was 2 nM 3,3’,5-triido-D-thyronine (Sigma), 0.4 μg/ml hydrocortisone evaluated using the Agilent 2100 Bioanalyzer system (Agilent (Sigma), 0.1 nM cholera toxin (Sigma), 10 ng/ml EGF (Austral Technologies Inc, Palo Alto, CA, USA). Biologicals, San Ramon, CA, USA), 24 μg/ml adenine, 10% fetal Two micrograms of total RNA from each sample were used to bovine serum (HyClone, Logan, UT, USA) and 50 μg/ml gentamicin. prepare biotinylated fragmented cRNA according to the GeneChip® NOKs in passage 2-5 were used. Fibroblasts were isolated from the Expression Analysis Technical Manual (Rev. 5; Affymetrix Inc., dermal compartment by treatment with collagenase and subcultured in Santa Clara, CA, USA). Affymetrix GeneChip® expression arrays DMEM with 10% bovine calf serum (HyClone) and 50 μg/ml ( U133 Plus 2.0 Array) were hybridized for 16 h in gentamicin. Subconfluent cells were washed with PBS and detached a 45˚C incubator, rotated at 60 rpm. In accordance with the with trypsin. Cells in passage 1-5 were used for the experiments. GeneChip® Expression Analysis Technical Manual (Rev. 5;

3254 Hakelius et al: Differential Gene Regulation in Fibroblasts

Affymetrix Inc.) the arrays were then washed and stained using the Table I. Summary of differentially regulated fibroblast transcripts and Fluidics Station 450 and finally scanned using the GeneChip® genes in co-cultures with either normal oral keratinocytes or head and Scanner 3000 7G. neck squamous cell carcinoma cells. Up-regulation indicates higher expression in head and neck squamous cell carcinoma cell co-cultures. Microarray data analysis. Subsequent analysis of the gene expression data was carried out in the freely available statistical Transcripts Unique genes computing language ="tag">R (www.r-project.org) using packages available from the Bioconductor project (www.bioconductor.org). The raw Total 33,544 16,010 p< data were normalized using the robust multi-array average (RMA) Regulated with an adjusted 0.05 345 290 Up-regulated 152 126 (12) method first suggested by Li and Wong in 2001 (13); all Down-regulated 193 164 functions used are available in the ‘affy’(14) and ‘affyPLM’ Regulated with an adjusted p<0.05 packages. At this point, probe sets with low level expression and a 2-fold change in expression 82 70 intensities of less than 5.0 were removed from the microarrays. In Up-regulated 30 27 order to search for genes that were differentially expressed between Down-regulated 52 43 co-cultures with SCC cells and with NOKs, an empirical Bayes’ moderated t-test was then applied using the ‘limma’ package (15). To address the problem with multiple testing, the p-values were adjusted using the method of Benjamini and Hochberg (16). False discovery rate (FDR) q-values are given. Those which also exhibited an average fold change of at least 2.0 requirement (Table II). As seen in Figure 1B, the hierarchical were visualized by heat-maps using Gene-E, freely available at clusters were well-maintained in this subset of genes. http://www.broadinstitute.org. The DAVID resources 6.7 (the for There were five well-defined gene hierarchy clusters Annotation, Visualization and Integrated Discovery), freely available (Figure 1B). The first hierarchy cluster included 12 gene at david.abcc.ncifcrf.gov/, was used for functional classification of transcripts characterized by a decreased expression in co- genes (17, 18) and also for functional annotation of differentially cultures with NOKs and a variable in SSC cell expressed genes into (GO) categories or according co-cultures. A second hierarchy cluster of 19 different gene to Biocarta pathways (cgap.nci.nih.gov/Pathways/BioCarta_ transcripts was characterized by a higher transcription in Pathways) or the enriched Kyoto Encyclopedia of Genes and NOK co-cultures than in fibroblasts alone and a lower Genomes (KEGG) pathways (www.genome.jp/kegg/). Finally, Gene Set Enrichment Analysis (GSEA) with analysis of transcription in SSC cell co-cultures. The remaining the leading edge (19) was used to determine similarities in gene transcripts were divided into three hierarchy clusters, one expression profiles with publicly available Molecular Signatures with 21 genes characterized by an increased transcription Database (MSigDB) gene sets using the freely available software at both in NOK cell co-cultures and in SSC co-cultures but www.broadinstitute.org. Data on individual genes were obtained more so in NOK co-cultures. Six gene transcripts were only from www..org. up-regulated in SSC co-cultures. Finally, 11 gene transcripts were strongly up-regulated both in NOK and in SCC co- Results cultures but more so in SCC co-cultures. These results imply that a differential regulation of gene expression between SSC High-resolution Affymetrix gene expression arrays were and NOK co-cultures involves genes that are either down- performed with the intention of discerning differences in the and or up-regulated in relation to the expression in way SSCs and NOKs affect gene expression in co-cultivated fibroblasts not exposed to any of those cells. fibroblasts. After robust multi-array average normalization and Using the DAVID Gene Functional Classification Tool, log transformation, we found that 345 of the total of 33,544 four different enriched functional gene clusters were studied transcripts were differentially regulated using a cut-off identified among the 152 gene transcripts that were at an adjusted p-value <0.05; 152 were up-regulated, i.e. with expressed higher in SCCs than in NOKs. The first cluster a higher expression in co-cultures with SCC than with NOKs contained genes for procollagens types I, III and V (Table and 193 were down-regulated (Table I). This corresponded to III). The second cluster contained the gene for interleukin 17 16,010 unique genes, whereof 290 were regulated; 126 were receptor B, with a gene product that mediates the activation up-regulated and 164 were down-regulated. of NF-ĸB and the production of IL8 that is up-regulated in After clustering the 290 regulated genes according to their inflammation and also in co-cultures with keratinocytes (7), gene expression profiles (Figure 1A), the three experimental as well as genes with largely unknown functions like the groups were well-separated into hierarchical clusters. To solute carrier family 22, member 23. One of those, the obtain a better focus over the most enriched genes, we 16 open reading frame 13, is over-expressed in separately analyzed those which were also regulated more cancer tissues (20). The third cluster contained genes for than 2-fold. Eighty-two transcripts, corresponding to 70 histone clusters 1 and 2. Finally, the fourth cluster contained unique genes, 27 up- and 43 down-regulated, fulfilled this genes for the ras-group of , among them the DIRAS3

3255 ANTICANCER RESEARCH 35: 3253-3266 (2015)

Table II. The 70 genes with more than 2log-fold change.

Probe ID Change1 adj.p

217590_s_at Transient receptor potential cation channel, subfamily A, member 1 1.71 0.015 206157_at Pentraxin 3, long 1.56 0.016 203666_at Chemokine (C-X-C motif) ligand 12 1.53 0.007 206025_s_at , alpha-induced 6 1.53 0.006 201939_at Polo-like kinase 2 1.49 0.009 206932_at Cholesterol 25-hydroxylase 1.49 0.009 215506_s_at DIRAS family, GTP-binding RAS-like 3 1.44 0.046 204439_at Interferon-induced protein 44-like 1.42 0.019 219869_s_at Solute carrier family 39 (zinc transporter), member 8 1.31 0.025 236313_at Cyclin-dependent kinase inhibitor 2B (p15, inhibits CDK4) 1.29 0.019 209840_s_at Leucine rich repeat neuronal 3 1.28 0.016 204224_s_at GTP cyclohydrolase 1 1.27 0.043 219872_at Family with sequence similarity 198, member B 1.25 0.028 223122_s_at Secreted frizzled-related protein 2 1.25 0.016 204897_at Prostaglandin E receptor 4 (subtype EP4) 1.21 0.030 221805_at Neurofilament, polypeptide 1.20 0.046 226658_at Podoplanin 1.12 0.030 202206_at ADP-ribosylation factor-like 4C 1.11 0.006 204301_at Kelch repeat and BTB (POZ) domain containing 11 1.11 0.015 233555_s_at Sulfatase 2 1.09 0.035 206101_at Extracellular matrix protein 2, female organ and adipocyte specific 1.09 0.036 205578_at Receptor tyrosine kinase-like orphan receptor 2 1.05 0.009 236858_s_at Runt-related 2 1.04 0.007 220108_at Guanine nucleotide binding protein (G protein), alpha 14 1.04 0.036 228153_at Ring finger protein 144B 1.03 0.015 205381_at Leucine rich repeat containing 17 1.01 0.049 204284_at Protein phosphatase 1, regulatory subunit 3C 1.01 0.009 204256_at ELOVL fatty acid elongase 6 –1.00 0.046 202627_s_at Serpin peptidase inhibitor, clade E (nexin, inhibitor type 1), member 1 –1.00 0.007 202345_s_at Fatty acid binding protein 5 (psoriasis-associated) –1.01 0.019 242871_at Progestin and adipoQ receptor family member V –1.02 0.013 226614_s_at Family with sequence similarity 167, member A –1.02 0.028 203373_at Suppressor of cytokine signaling 2 –1.02 0.034 212143_s_at Insulin-like growth factor binding protein 3 –1.02 0.036 201578_at Podocalyxin-like –1.02 0.027 224657_at ERBB receptor feedback inhibitor 1 –1.03 0.019 226550_at Solute carrier family 9, subfamily A (NHE7, cation proton antiporter 7), member 7 –1.03 0.009 203320_at SH2B adaptor protein 3 –1.03 0.019 218451_at CUB domain containing protein 1 –1.04 0.007 230425_at EPH receptor B1 –1.04 0.027 209457_at Dual specificity phosphatase 5 –1.04 0.027 206298_at Rho GTPase activating protein 22 –1.05 0.006 212801_at Citron (rho-interacting, serine/threonine kinase 21) /// microRNA 1178 –1.05 0.020 204823_at Neuron navigator 3 –1.05 0.015 217979_at Tetraspanin 13 –1.07 0.035 222740_at ATPase family, AAA domain containing 2 –1.09 0.041 209990_s_at Gamma-aminobutyric acid (GABA) B receptor, 2 –1.09 0.023 219789_at Natriuretic peptide receptor C/guanylate cyclase C (atrionatriuretic peptide receptor C) –1.10 0.036 203889_at Secretogranin V (7B2 protein) –1.14 0.007 225655_at Ubiquitin-like with PHD and ring finger domains 1 –1.15 0.019 223700_at Meiotic nuclear divisions 1 homolog (S. cerevisiae) –1.15 0.035 208893_s_at Dual specificity phosphatase 6 –1.16 0.015 228069_at Family with sequence similarity 54, member A –1.17 0.035 219990_at E2F transcription factor 8 –1.18 0.044 227458_at CD274 molecule –1.20 0.019 207505_at Protein kinase, cGMP-dependent, type II –1.23 0.032 230372_at Hyaluronan synthase 2 –1.25 0.019 201890_at Ribonucleotide reductase M2 –1.27 0.026

Table II. Continued

3256 Hakelius et al: Differential Gene Regulation in Fibroblasts

Table II. Continued

Probe ID Change1 adj.p

213506_at Coagulation factor II () receptor-like 1 –1.27 0.041 224320_s_at Minichromosome maintenance complex component 8 –1.30 0.019 229551_x_at Zinc finger protein 367 –1.30 0.011 201042_at Transglutaminase 2 (C polypeptide, protein-glutamine-gamma-glutamyltransferase) –1.31 0.035 217428_s_at Collagen, type X, alpha 1 –1.37 0.027 235518_at Solute carrier family 8 (sodium/calcium exchanger), member 1 –1.48 0.009 208394_x_at Endothelial cell-specific molecule 1 –1.64 0.041 214841_at Cornichon homolog 3 (Drosophila) /// uncharacterized LOC100506354 –1.64 0.007 237252_at –1.86 0.011 209821_at –1.92 0.038 206924_at –2.01 0.041 215034_s_at Transmembrane 4 L six family member 1 –2.03 0.010

12log-fold change.

protein, suggested to be a tumor suppressor gene (21) and enrichment with an FDR of p<0.001, whereof 98 were the interferon inducible guanylate binding protein 2. positively enriched and 200 negatively enriched. Fifty-four There were five functional gene clusters of the transcripts genes appeared in more than 10 of the positively enriched that were less expressed in SCCs than in NOKs. The first sets (Table V). Among these, more than 25 are related to four clusters largely coded for proteins involved in cell-cycle interferon signaling, more than 35 to an innate response in a regulation control, while the fifth cluster also included genes wider sense and more than 11 to connective tissue function. for cell-surface and extracellular proteins, e.g. hyaluronan A clustered heat map (Figure 2, blue) showed that the synthase-2. negatively enriched genes were evenly distributed in most In a functional annotation analysis using Gene Ontology gene sets. In contrast, the positively enriched genes appeared categories, up-regulated genes were all related to in more defined subgroups of the gene sets (Figure 2 in red). differentiation and organization, while down-regulated A further analysis of the heat map revealed that most genes genes were related to cell cycle-related events (data not related to interferon response, the innate response in general shown). In a functional annotation analysis clustering based and genes directly related to production of ECM discussed on the same categories, there were no less than 14 up- above were clustered in three clusters, with only a partial regulated and 12 down-regulated clusters of down-regulated overlap between gene sets (Figure 2). genes (data not shown). The most up-regulated cluster contained genes related to the ontologies “collagen”, Discussion “proteinaceous extracellular matrix” and “extracellular matrix part”. In a similar clustering based on pathway We have shown that there is a differential regulation of gene assignments and protein domains, the most enriched cluster expression in fibroblasts caused by humoral signaling from of up-regulated genes contained genes related to collagen an oral SCC line compared to that from normal oral and the extracellular matrix. keratinocytes. Two apparent and different observations were Two strategies were used to search for similarities in gene an enrichment of genes related to a fibroblastic behavior of expression with publicly-presented gene sets using the GSEA the fibroblast, i.e. related to synthesis of collagens types I, software. We first searched the MSigDB with the keyword III and V, and genes related to an innate-like response, e.g. in “fibroblasts” and obtained 135 gene sets. These were the form of pentraxin-3. imported into the GSEA software together with the ranked As the aim of the study was to investigate overall list from the array based on fold change. Sixty-five of those differences in wide gene expression patterns rather than gene sets were positively enriched and 58 were negatively changes in expression of individual genes, no attempts were enriched. Data from the 20 most enriched sets for both made to confirm the regulation of individual genes with a phenotypes, up-regulated and down-regulated, are seen in corresponding modulation in protein expression. Table IV. Nevertheless, such broad effects on gene expression pattern We, thereafter, searched for similarities versus all curated were verified. gene sets of the MSigDB and included a leading edge Direct cell-to-cell contact between tumor cells and stromal analysis of the 298 gene sets that exhibited a significant fibroblasts induces the expression of collagens and MMP1

3257 ANTICANCER RESEARCH 35: 3253-3266 (2015)

Figure 1. Heat map and hierarchical clustering of the 290 regulated fibroblast genes (A) and those 70, which -in addition- exhibited more than a 2- fold change (B). Three experimental groups were run in triplicates. SSC, squamous cell carcinoma cells in insert; NOK, normal oral keratinocytes in insert; F, fibroblasts only. The heat maps are normalized to the mean of the “F-groups”.

in fibroblasts (22). Typical expression patterns of tissue dynamics of the humoral factors released by SCC as well as factor, PAI-I, and uPA also require cell-to-cell contact, while NOKs are not known. Many of those factors can be supposed humoral communication alone induces a reciprocal response to be involved in a reciprocal interplay within and between (23). Direct cell-cell contact between tumor and stromal cells the cell types, whereas different time patterns may apply for are present during tumor invasion of the host (24). The different factors. Second, and related to this feature, is that present model system, using a semi-permeable membrane gene expression was only assessed at one time point, after separating the epithelial compartment from the fibroblast 24 h. It may, therefore, be that the time chosen was sub- compartment, was designed to study the interplay between optimal for discerning a possible differential expression in tumor and stromal cells at an earlier stage, during the first early, as well as late, expressed genes. pre-invasion phase of a tumor. This is characterized by There is currently firm evidence that phenotypically specific cellular changes in the transformed epithelium, modified fibroblasts, the CAFs, play an important role for which is still resting on an intact basal membrane. At this tumor growth and progression (3, 25, 26). Gene expression stage, any epithelial-stromal interactions over this barrier are profiling has previously demonstrated significant differences bound to occur by humoral means. between CAFs and normal fibroblasts (27). Of relevance is Two characteristics of the experimental setting are that conditioned medium from tumor cells induced a CAF- important to consider. First, the temporal concentration like phenotype and an expression pattern similar to the

3258 Hakelius et al: Differential Gene Regulation in Fibroblasts

Figure 2. Clustered heat map of the leading edge analysis where genes that are regulated in multiple gene sets are identified and labeled. The complete map is seen at the utmost left, magnified excerpts of interest in the middle and, further magnified, the corresponding gene symbols at the utmost right. The different genes are shown on the vertical axis, while the 298 enriched and clustered gene sets are seen on the horizontal axis with the positively clustered sets to the left and the negatively clustered to the right. The vertical line in the middle frame discriminates gene sets related to ECM turnover, right of line, from those related to interferon activation, left of line. I, II and III represent the gene clusters that were defined as “innate response”, “ECM-response” and “IFN-response”. See Table V.

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Table III. Functional classification of regulated genes using the DAVID bioinformatics resources.

Up-regulated genes; n=152 228401_at ATPase family, AAA domain containing 2 Gene Group 1 222740_at ATPase family, AAA domain containing 2 201852_x_at, Collagen, type III, alpha 1 205394_at CHK1 checkpoint homolog (S. pombe) 232458_at Collagen, type III, alpha 1 222843_at Fidgetin-like 1 202404_s_at Collagen, type I, alpha 2 204825_at Maternal embryonic leucine zipper kinase 202310_s_at Collagen, type I, alpha 1 208795_s_at Minichromosome maintenance 221730_at Collagen, type V, alpha 2 Complex component 7 221729_at Collagen, type V, alpha 2 209464_at Aurora kinase B 224320_s_at Minichromosome maintenance Gene Group 2 Complex component 8 221901_at KIAA1644 224361_s_at Interleukin 17 receptor B Gene Group 4 224156_x_at Interleukin 17 receptor B 229551_x_at Zinc finger protein 367 219255_x_at Interleukin 17 receptor B 209054_s_at Wolf-Hirschhorn syndrome candidate 1 219872_at Chromosome 4 open reading frame 18 228964_at PR domain containing 1, with ZNF domain 219700_at Plexin domain containing 1 209120_at Nuclear receptor subfamily 2, group F, member 2 223194_s_at Solute carrier family 22, member 23 225655_at Ubiquitin-like with PHD and ring finger domains 1 238520_at Transcriptional regulating factor 1 Gene Group 3 213435_at SATB homeobox 2 209806_at Histone cluster 1, H2bk 223274_at Transcription factor 19 215071_s_at Histone cluster 1, H2ac 209911_x_at Histone cluster 1, H2bd Gene Group 5 202708_s_at Histone cluster 2, H2be 209386_at Transmembrane 4 L six family member 1 218280_x_at Histone cluster 2, H2aa3; histone cluster 2, H2aa4 215034_s_at Transmembrane 4 L six family member 1 214290_s_at Histone cluster 2, H2aa3; histone cluster 2, H2aa4 221901_at KIAA1644 214772_at open reading frame 41 Gene Group 4 201324_at Epithelial membrane protein 1 219210_s_at RAB8B, member RAS oncogene family 201325_s_at Epithelial membrane protein 1 230266_at RAB7B, member RAS oncogene family 213895_at Epithelial membrane protein 1 215506_s_at DIRAS family, GTP-binding RAS-like 3 229011_at Epithelial membrane protein 1 242907_at Guanylate binding protein 2, interferon-inducible 232263_at Solute carrier family 6 (neutral transporter), member 15 219985_at Heparan sulfate (glucosamine) Down-regulated genes; n=193 3-O-sulfotransferase 3A1 Gene Group 1 223533_at Leucine rich repeat containing 8 family, member C 204026_s_at ZW10 interactor 212906_at GRAM domain containing 1B 212789_at Non-SMC condensin II complex, subunit D3 242871_at Progestin and adipoQ receptor family member V 219000_s_at Defective in sister chromatid cohesion 1 homolog 218451_at CUB domain containing protein 1 (S. cerevisiae) 234932_s_at CUB domain containing protein 1 208025_s_at High mobility group AT-hook 2 225295_at Solute carrier family 39 (zinc transporter), 223307_at Cell division cycle associated 3 Member 10 219588_s_at Non-SMC condensin II complex, subunit G2 234994_at Transmembrane protein 200A 217640_x_at Chromosome 18 open reading frame 24 207038_at Solute carrier family 16, Member 6 (monocarboxylic acid transporter 7 Gene Group 2 223092_at Ankylosis, progressive homolog (mouse) 226283_at WD repeat domain 51B 214841_at Cornichon homolog 3 (Drosophila) 204775_at Chromatin assembly factor 1, subunit B (p60) 225707_at ADP-ribosylation-like factor 6 interacting protein 6 218585_s_at Denticleless homolog (Drosophila) 225711_at ADP-ribosylation-like factor 6 interacting protein 6 209789_at Coronin, actin binding protein, 2B 230372_at Hyaluronan synthase 2 206432_at Hyaluronan synthase 2 Gene Group 3 201136_at Proteolipid protein 2 (colonic epithelium-enriched) 207505_at Protein kinase, cGMP-dependent, type II 209170_s_at Glycoprotein M6B 223229_at Ubiquitin-conjugating E2T (putative) 225673_at Myeloid-associated differentiation marker 203755_at Budding uninhibited by benzimidazoles 1 homolog 212858_at Progestin and adipoQ receptor family member IV beta (yeast) 201578_at Podocalyxin-like 219494_at RAD54 homolog B (S. cerevisiae) 217979_at Tetraspanin 13 212801_at Citron (rho-interacting, serine/threonine kinase 21) 208079_s_at Aurora kinase A; aurora kinase A 1 203856_at Vaccinia related kinase 1 218782_s_at ATPase family, AAA domain containing 2

3260 Hakelius et al: Differential Gene Regulation in Fibroblasts

Table IV. Characteristics of the 20 most enriched GSEA human fibroblast data sets. FDR<0.01

Challenge Reference NES1

Phenotype up After exposure to serum; three gene sets (31) 1.73-2,70 After exposure to IR radiation; two gene sets (44) 2.14-2.40 Immortalized fibroblasts (45) 2.37 Fibroblasts from Rett syndrome (46) 2.17 CMV infection; three gene sets (47) 1.66-2.13 Effect of gamma and UV radiation; two gene sets (48) 2.03-2.05 Hypertrophic scar fibroblasts response to IL6 (49) 2.02 Telomerase modification of embryonic fibroblasts (50) 1.93 Immortalized fibroblasts in the (51) 1.91 KEGG Gene set Asthma (52) 1.77 CAF-like differentiation of human mesenchymal stem cells (28) 1.74 Effect of TGFβ1 (53) 1.74 Effect of DNA damage (48) 1.64 Corneal fibroblast response to IL-1α (30) 1.64

Phenotype down After exposure to serum; four gene sets (31) –2.40-–3.45 Effect of ionizing radiation (54) –3.44 Effect of IE86 CMV protein (55) –3.12 Cell cycle related (56) –2.98 Effect of UV-radiation; three gene sets (57) –1.71-–2.61 DNA changes related to age; three gene sets (58) –2.52-–2.58 Effects of cisplatin (59) –2.17 Effect of UV –radiation on xeroderma fibroblasts (60) –1.87 Hypertrophic scar fibroblasts response to IL-6 (49) –1.65

1Normalized enrichment score.

differential expression observed in this study, in cultured with SCCs, thus, supports the concept that this mesenchymal stem cells (28), . molecule is involved in an autocrine signaling loop that gives Prior studies from this laboratory point to the importance rise to tumor-promoting CAF myofibroblasts during tumor of IL-1α released from the epithelial cells for the fibroblast progression (32). Likewise, tumor necrosis factor alpha- response, observed as regulation of genes related to induced protein 6, TNFAIP6, a member of the hyaluronan- connective tissue turnover (6, 29). A more general effect on binding , is involved in extracellular matrix gene expression in fibroblasts is supported by expression stability and cell migration and is suggested to have a role studies in corneal fibroblasts (30), where exposure to IL-1α in the negative feedback control of the inflammatory led to an expression profile similar to the differential response (33). expression observed in this study. There was an increased expression of both IL-11 and IL- This study was conducted in an environment with only 33 in co-cultures with both NOKs and SCCs, although more 0.5 % normal calf serum. This concentration was chosen to so in those with NOKs (Figure 1). IL-11 is part of an NFĸB- maximally reduce the dosage of exogenous growth factors mediated response (34, 35) known to be produced by while maintaining a milieu that allows cell viability. Another fibroblasts stimulated by both IL-1 and TGF-beta, with a important aspect is that serum contains components normally synergistic effect (36). IL-33, a member of the IL-1 family not present in healthy tissues in vivo and reflects a wound- (37), is induced by TNF-α and IL-1 and is normally not like environment (31). This strategy optimizes the possibility present in fibroblasts from normal human tissues (38). of revealing growth stimulatory and inhibitory effects due to Rather, its expression has been linked to a conversion of humoral signaling from co-cultured cell types. resting fibroblasts to a contractile myofibroblast-like Some of the genes that were differentially expressed in co- phenotype (39). cultures with SCCs compared to NOKs were related to a The expression of pentraxin 3 (PTX3) was restricted to malignant stromal phenotype. The up-regulation of co-cultures with SSC (Figure 1). PTX3 is recognized as chemokine (C-X-C motif) ligand 12 in fibroblasts co- playing a role in the (40) and is

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Table V. The 54 genes that appear in more than 10 of the gene sets in the leading edge analysis. Gene characteristics are taken from http://www.genecards.org/ and genes associated with an interferon response, ECM proteins and innate response in a wider sense are shaded. Genes located in the clusters shown in the heat map of Figure 2 are marked with a “1”.

Gene symbol Description No. of Cluster 1/ Cluster II/ Cluster III/ gene sets IFN-response ECM Innate response

IFIT1 IFN-induced protein with tetratricopeptide repeats 1 30 ISG15 Ubiquitin-Like Modifier; IFN-Induced 15 KDa Protein 30 IFIT3 IFN-induced protein with tetratricopeptide repeats 3 29 STAT1 Signal transducer and activator of transcription 1, 91kDa 27 COL3A1 Collagen, Type III, Alpha 1 26 1 MX1 Myxovirus (Influenza Virus) Resistance 1, IFN-inducible Protein P78 26 1 OAS1 2'-5'-Oligoadenylate Synthetase 1 24 1 OAS2 2'-5'-Oligoadenylate Synthase 2 24 1 GBP1 Guanylate Binding Protein 1, IFN-Inducible 23 1 IFI35 IFN-Induced Protein 35 22 1 IFIT2 IFN-induced protein with tetratricopeptide repeats 2 22 1 COL1A2 Collagen, Type I, Alpha 2 20 COL5A2 Collagen, Type V, Alpha 2 20 1 IFI27 IFN1 alpha-inducible protein 27 19 1 IFITM1 IFN induced transmembrane protein 1 19 1 MX2 Myxovirus (influenza virus) resistance 2 (mouse) 19 1 C1S Complement Component 1, S Subcomponent; 18 1 COL1A1 Collagen, Type I, Alpha 1 18 1 FBN1 Fibrillin 1 18 1 OASL 2'-5'-Oligoadenylate Synthase-Like Protein; 18 1 TRIM22 Tripartite Motif Containing 22; induced by IFNs 18 1 IFI44L IFN-induced protein 44-like 17 1 IFI6 IFN, alpha-inducible protein 6 17 1 IFIH1 IFN induced with C domain 1 17 1 LOX 17 1 LGALS3BP Lectin, Galactoside-binding, Soluble, 3 Binding Protein 16 1 CCL2 Chemokine (C-C motif) ligand 2 15 1 COL5A1 Collagen, Type V, Alpha 1 15 1 SOD2 Superoxide Dismutase 2, Mitochondria 15 1 CDH11 Cadherin 11, type 2, OB-cadherin (osteoblast) 14 1 FAS Fas cell surface death receptor 14 1 IRF1 IFN regulatory factor 1 14 1 IRF7 IFN regulatory factor 7 14 1 POSTN , osteoblast specific factor 14 1 CFB 13 IFI44 IFN-induced protein 44 13 1 PSMB9 Proteasome (prosome, macropain) subunit, beta type 13 1 PTX3 Pentraxin 3, long 13 RARRES3 Retinoic acid receptor responder (tazarotene induced) 3 13 TNFAIP6 Tumor necrosis factor, alpha-induced protein 6 13 USP18 Ubiquitin specific peptidase 18 13 BST2 Bone marrow stromal cell antigen 2 12 1 MARCKS Myristoylated alanine-rich protein kinase C substrate 12 TSC22D3 TSC22 domain family, member 3 12 BCL6 B-cell CLL/lymphoma 6 11 CALD1 1 11 CLU 11 CXCL14 Chemokine (C-X-C motif) ligand 14 11 DCN 11 GCH1 GTP cyclohydrolase 1 11 GPNMB Glycoprotein (transmembrane) nmb 11 IFIT5 IFN-induced protein with tetratricopeptide repeats 5 11 1 SP110 SP110 nuclear body protein 11 1 THBS2 Thrombospondin 2 11

1IFN, Interferon.

3262 Hakelius et al: Differential Gene Regulation in Fibroblasts identified as an IL-1-inducible gene in endothelial cells (EC) 9 Grenman R, Pekkola-Heino K, Joensuu H, Aitasalo K, Klemi P and a TNF-stimulated gene in fibroblasts (41). It is a and Lakkala T: UT-MUC-1, a new mucoepidermoid carcinoma phylogenetically old molecule the activation of which cell line, and its radiosensitivity. Arch Otolaryngol Head Neck Surg 118: 542-547, 1992. reflects an unspecific response to cell damaging stimuli (42). 10 Rheinwald JG: Serial cultivation of normal human epidermal An important observation is that many of the genes keratinocytes. Methods Cell Biol pp. 229-254, 1980. identified in the leading edge of the GSEA analysis were 11 Chomczynski P: A reagent for the single-step simultaneous related to an innate response in its widest sense, to interferon isolation of RNA, DNA and proteins from cell and tissue signaling (43) or to connective tissue turnover. Interestingly, samples. Biotechniques 15: 532-534, 536-537, 1993. as seen in Figure 2, the enriched gene sets that presented 12 Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis with interferon genes in the leading edge were different from KJ, Scherf U and Speed TP: Exploration, normalization, and those that presented with connective tissue-related genes. We summaries of high density oligonucleotide array probe level data. Biostatistics 4: 249-264, 2003. hypothesize that one possible factor, not taken into 13 Li C and Wong WH: Model-based analysis of oligonucleotide consideration in this study, is related to the time aspect of arrays: expression index computation and outlier detection. Proc gene activation. It is noteworthy that the gene sets that Natl Acad Sci USA 98: 31-36, 2001. exhibited a PTX3 response are different from those with an 14 Gautier L, Cope L, Bolstad BM and Irizarry RA: affy--analysis interferon gene-related response. of Affymetrix GeneChip data at the probe level. Bioinformatics 20: 307-315, 2004. Acknowledgements 15 Smyth GK: Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3: Article3, 2004. The Authors would like to thank Professor Reidar Grénman, Turku 16 Benjamini Y and Hochberg Y: Controlling the False Discovery University, Finland, for providing the tumor cell line. They also Rate: A Practical and Powerful Approach to Multiple Testing. J thank Ms. Marja Bostrom for excellent technical support and the R Statist Soc B 57: 289-300, 1995. Thureus foundation and the Swedish Cancer Foundation for funding. 17 Huang da W, Sherman BT and Lempicki RA: Bioinformatics enrichment tools: paths toward the comprehensive functional References analysis of gene lists. 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